/Personal-Loan-Modelling

We have to predict whether a customer will respond to a Personal Loan Campaign!

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Personal-Loan-Modelling

Data Description:

The file Bank_Personal_Loan_Modelling.csv contains data on 5000 customers. The data include customer demographic information (age, income, etc.), the customer's relationship with the bank (mortgage, securities account, etc.), and the customer response to the last personal loan campaign (Personal Loan). Among these 5000 customers, only 480 (= 9.6%) accepted the personal loan that was offered to them in the earlier campaign.

Attribute Information:

ID : Customer ID

Age : Customer's age in completed years

Experience : No. of years of professional experience

Income : Annual income of the customer ($ 000)

ZIP Code : Home Address Zip Code

Family : Family size of the customer

CCAvg : Avg. Spending on Credit Card per Month ($ 000)

Education : Education Level. 1: Undergrad; 2: Graduate; 3: Advanced / Professional

Mortgage : Value of house mortgage if any. ($000)

Personal Loan : Did this customer accept the personal loan offered in the last campaign?

Securities Account : Does the customer have a securities account with the bank?

CD Account : Does the customer have a certificate of deposit (CD) account with the bank?

Online : Does the customer use internet banking facilities?

Credit card : Does the customer use a credit card issued by this Bank?